Using Brain Signals To Read Emotions

The image on the left shows what happy looks like in the brain; the image on the right shows what sad looks like in the brain (credit: Karim S. Kassam et al./Carnegie Mellon University)

Charles Darwin believed that emotions give a purpose to humans - by helping them communicate and survive. In 1884 the American philosopher and psychologist William James said an exciting fact would lead directly to a physiological response which was known to us as emotion.

To explain away different emotional experiences, James proposed that a set of stimuli trigger activity in the autonomic nervous system, which then produces an emotional experience in the brain.

The word "emotion" goes way back to 1579 adapted from the French émouvoir, which means "to stir up". Emotions have been described as discrete and consistent responses to internal or external events which have a particular significance for the organism.

Feelings and emotions - murky waters. Scientific research is based on what you can prove by measurement. So, research on emotions is slow going because there aren't reliable methods to actually measure or evaluate them and emotions can also be triggered by something else. And then, there's the human element -- we tend, as humans, not to really report our feelings honestly.

In short, they were able to identify which emotions (happy, sad, envy, disgust, lust) a person is experiencing based on their brain activity as well as insight into how the brain catagorizes feelings.

Surprising results? Yes, the research team found that positive and negative emotions have distinct neural signatures - that it was easiest to identify happiness and least accurate in identifying envy. They also discovered that lust was the least likely emotion to be misidentified suggesting that lust produces a pattern of neural activity that's distinct from all other emotional experiences.

To complete the research, the scientists needed a control group. For the study, they found 10 actors who elected to be scanned at CMU’s Scientific Imaging & Brain Research Center . They viewed the words of nine emotions: anger, disgust, envy, fear, happiness, lust, pride, sadness and shame while they were inside the fMRI scanner and were instructed to enter each of these emotional states multiple times, in random order.

To make sure the technique was measuring emotions and not the act of trying to induce an emotion in oneself, the researchers also presented participants with pictures of neutral and disgusting photos they hadn't seen before.

According to the press release, the computer model, which was constructed from using statistical information to analyze the fMRI activation patterns that were created for 18 emotional words then "learned the emotion patterns from self-induced emotions and could correctly identify the emotional content of photos being viewed using the brain activity of the viewers."

The press release also stated that "the computer model achieved a rank accuracy of 0.84. Rank accuracy is the percentile rank of the correct emotion in an ordered list of the computer model guesses; random guessing has accuracy rate of 0.50.

“This research introduces a new method with potential to identify emotions without relying on people’s ability to self-report,” said Karim Kassam, assistant professor of social and decision sciences and lead author of the study. “It could be used to assess an individual’s emotional response to almost any kind of stimulus, for example, a flag, a brand name or a political candidate.”